Predictive Modeling Applications in Actuarial Science
 Volume 1
 Introduction
 Predictive Modeling Foundations
 Predictive Modeling Methods
 Bayesian and Mixed Modeling
 Longitudinal Modeling
 Volume 2
 Generalized Linear Model
 Extensions of the Generalized Linear Model
 Unsupervised Predictive Modeling Methods

Applications on Current Problems in Actuarial Science
 Chapter 8  The Predictive Distribution of Loss Reserve Estimates over a Finite Time Horizon
 Chapter 9  Finite Mixture Model and Workersâ€™ Compensation LargeLoss Regression Analysis
 Chapter 10  A Framework for Managing Claim Escalation Using Predictive Modeling
 Chapter 11  Predictive Modeling for UsageBased Auto Insurance
Volume 1 Description
Volume 1 will lay out the foundations of predictive modeling.
Beginning with reviews of regression and time series methods, this book will provide stepbystep introductions to advanced predictive modeling techniques that are particularly useful in actuarial practice. Readers will gain expertise in several statistical topics, including generalized linear modeling, the analysis of longitudinal, twopart (frequency/severity) and fattailed data. Thus, although the audience is primarily professional actuaries, we have in mind a “textbook” approach and so this volume will also be useful for continuing professional development.
To get the most out of this book, readers should have familiarity with multiple linear regression methods such as found in Frees (2010), Regression Modeling with Actuarial and Financial Applications. This book provide the common notation that will be used by chapter authors.
Volume 2 Description
Volume 2 examines applications of predictive modeling. Where Volume 1 developed the foundations of predictive modeling, Volume 2 explores practical uses for techniques, focusing especially on property and casualty insurance. Readers are exposed to a variety of tech niques in concrete, reallife contexts that demonstrate their value, and the overall value of predictive modeling, for seasoned practicing analysts as well as those just starting out.
Table of Contents
Volume 1
 Predictive Modeling in Actuarial Science
 Overview of Linear Models
 Regression with Categorical Dependent Variables
 Regression with Count Dependent Variables
 Generalized Linear Models
 Frequency and Severity Models
 Longitudinal and Panel Data Models
 Linear Mixed Models
 Credibility and Regression Modeling
 FatTail Regression Models
 Spatial Statistics
 Unsupervised Learning
 Bayesian Computational Methods
 Bayesian Regression Models
 Generalized Additive Models and Nonparametric Regression
 NonLinear Mixed Models
 Time Series Analysis
 Claims Triangles/Loss Reserves
 Survival Models
 Transition Modeling
Introduction
Predictive Modeling Foundations
Predictive Modeling Methods
Bayesian and Mixed Modeling
Longitudinal Modeling
Volume 2
 Pure Premium Modeling Using Generalized Linear Models
 Applying Generalized Linear Models to Insurance Data: Frequency/Severity versus Pure Premium Modeling
 Generalized Linear Models as Predictive Claim Models
 Frameworks for General Insurance Ratemaking: Beyond the Generalized Linear Model
 Using Multilevel Modeling for Group Health Insurance Ratemaking: A Case Study from the Egyptian Market
 Clustering in General Insurance Pricing
 Application of Two Unsupervised Learning Techniques to Questionable Claims: PRIDIT and Random Forest
 The Predictive Distribution of Loss Reserve Estimates over a Finite Time Horizon
 Finite Mixture Model and Workersâ€™ Compensation LargeLoss Regression Analysis
 A Framework for Managing Claim Escalation Using Predictive Modeling
 Predictive Modeling for UsageBased Auto Insurance